The candidate has a Ph.D. in mathematics, with a strong research background in mathematical physics, including dynamical systems, differential equations, spectral theory, geometry etc. Since 1997 he has been working on an interdisciplinary biomedical study with the University of Virginia (UVA), establishing new bioanalytical tools for modeling of blood glucose fluctuations related to hypoglycemia in IDDM. In April 1999, the candidate joined the department of Internal Medicine at UVA, working on dynamic feedback control of the growth hormone (GH) axis. The studies resulted in the creation of a new deterministic model, describing the male rat GH secretory pattern, and shaped the foundation of the present research/training application. On a research level, we propose to investigate our general hypothesis that a parsimonious feedback model can approximate the secretory pattern in both male and female rats, with the observed gender differences explained solely by parameter transitions. The model will be tested/refined using data collected by other projects and will be further extended to approximate the GH release network in the human. We believe that the results will offer new insights into the functional organization of the neuroendocrine hypothalamo-pituitary mechanisms that mediate the dynamic activity of the GH axis. On a training level, the candidate's immediate goal is to establish a sufficient background in the field of hormone pulsatility that will promote his efforts to approach analytically problems related to GH release in the rodent and human. To meet this goal, the career development plan anticipates two formally different parts. The first half of the award period includes four basic medical courses combined with supervised research. The second half is dedicated exclusively to extensive supervised research in the framework of the research plan. The proposed four-year research/training will be performed at the UVA, a university with rich traditions and a large network of facilities supporting research and education in the life sciences. The candidate will interact extensively with outstanding scholars across multiple laboratories, which will help him to achieve the long-term goal of this award - to become an independent investigator able to apply advanced mathematics in biomedical research related to endocrinology.